> ## Content Index > Fetch the complete content index at: https://sanzstack.com/llms.txt > Use this file to discover other available public pages before exploring further. # What If Your ERP Could Turn WhatsApp Messages into Draft Sales Orders? - URL: https://sanzstack.com/what-if-your-erp-could-turn-whatsapp-messages-into-draft-sales-orders/ - Published: 2026-10-26T05:14:26.000Z - Updated: 2026-10-26T05:15:54.000Z - Author: Saravanan Arunagiri - Tags: Transport, Business Tools ## The Daily Problem: Customer Orders Arrive as Conversations In today’s AI-driven world, relying on manually written orders from salespeople keeps your business stuck in the past. While user-friendly software is widely available for non-technical users, many salespeople still prefer sending orders as WhatsApp text or voice messages. Consequently, team members must read through these messages and manually input draft orders for processing by other departments. Missing messages or whole conversations is a major daily issue, which often comes to light only when a client asks, “Why hasn’t my order been delivered yet?” > Note: I used AI to help draft and edit parts of this article. The ideas and examples are my own, and I reviewed the final text. ## The Idea: Turn an Order Message into a Draft Sales Order Integrate an AI chatbot with your preferred messaging channels — such as WhatsApp, Telegram, Instagram, or a custom website bot — and connect it directly to your existing order management systems, including SAP, Zoho, CRMs, or other business software. ## How the Workflow Could Work 1. **Identify Customer —** Identify customer details from incoming message **2\. Extract Product Details-** Parse items, quantities, and specifications **3\. Match with Existing database —** Cross-reference items with inventory/ERP database **4\. Flag Missing / Failed Items-** Highlight unmatched products or incomplete info 5\. **Approve Order —** Review and grant final authorization **6\. Order Complete-** Order finalized and confirmation sent to customer ## Identify Customer Locate and verify the customer record in the database using unique identifiers such as their phone number or email address. **Proactive Balance Sharing:** Where feasible, providing customers with their current outstanding invoice balance prior to order placement enables them to review their account status and make informed purchasing decisions. ## Extract Products, Quantities and Delivery Details The system extracts key product information from incoming messages, capturing details such as product name, unit of measure (UOM), quantity, and requested delivery date. Because customers frequently send multiple messages for a single order, the system maintains a draft of the order in memory as inputs arrive. Once all information is gathered, it generates a summary for customer approval. If any required details are missing — for example, if a customer requests an item without specifying quantity or delivery timelines — the system automatically prompts the user for the necessary inputs to ensure a complete order. ## Matching Customer Language to Your Product Database Extracting the product name is only the first step. The next challenge is identifying which item the customer actually means. A customer might request **“premium basmati,”** while your database stores the product as **“Royal Harvest Basmati Rice, Premium Grade, 5 kg.”** Customers often use shortened names, familiar terms, abbreviations or spelling variations rather than your exact product descriptions. The system could combine keyword search, known customer aliases and AI-based similarity matching to suggest relevant items. It should also consider details such as brand, grade, pack size and the customer’s previous orders. However, a close match is not always the correct match. If the database contains several premium basmati products, the system should ask a specific question: ![Write on Medium](https://sanzstack.com/content/images/2026/10/Several-messages--one-complete-draft.png) “Do you mean Royal Harvest Premium Basmati Rice in the 5 kg pack or the 25 kg bag?” Once the item is confirmed, the draft order can use its actual ERP item code and ordering unit. A request for “five bags” also needs clarification if the product comes in multiple bag sizes. Confirmed customer terminology can be saved as a customer-specific alias for future orders, with appropriate review. **The goal is to find likely matches quickly, clarify ambiguity and prevent the wrong product from entering the order.** Instead of searching for the complete phrase, split it into individual words. **Customer input:** premium basmati **Search words:** premium, basmati Search for products containing **both words**, regardless of their order: > SELECT ItemCode, ProductName > FROM Products > WHERE ProductName LIKE '%' + @Word1 + '%' > AND ProductName LIKE '%' + @Word2 + '%'; Pass premium and basmati as parameter values. **Database product** **Result** Royal Premium Basmati Rice 5 kg — *Match* Basmati Rice Premium Grade 25 kg — *Match* Premium Jasmine Rice 5 kg - *No match* Before searching, convert punctuation to spaces, remove extra spaces and split the text. Keep useful details such as brand names and pack sizes. If multiple products match, ask the customer to choose. If nothing matches, search using **any word** (OR) to suggest candidates for review. **This handles different word orders, but spelling mistakes and alternative names need additional matching.** ## Flag Missing / Failed Items If any items are missing or cannot be matched, they should be flagged immediately for manual review to update the order. Swift action is essential to prevent unnecessary delays in order processing. ## Approve Order Once all details are verified, a final authorization converts the draft version into a active sales order. Advanced workflows can automate approvals for recurring orders from established clients. In such setups, manual review is required only when unusual order values or unfamiliar items are detected, significantly saving time for the approval team. ## Start Small, Review Carefully, Improve Gradually Turning WhatsApp messages into draft sales orders can reduce repetitive data entry, but success depends on more than extracting text. Business owners should first check whether their product catalogue, item codes and ordering units are accurate. Developers and product owners need to handle messages arriving in parts, product-name variations, missing details and changes to an existing request. Start with one common order format and a small group of customers. Let the system collect information, suggest matching products and ask questions when something is unclear. Ask the customer to confirm the summary, then keep a staff review step before creating the sales order. Measure the time saved, corrections required and frequency of clarification. Use those findings to decide what to improve next. A useful first version should make order entry easier while keeping people in control.